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--- |
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base_model: naufalihsan/indonesian-sbert-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- indonlu |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: sentiment |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: indonlu |
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type: indonlu |
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config: smsa |
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split: validation |
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args: smsa |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.95 |
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- name: Precision |
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type: precision |
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value: 0.9499758037063356 |
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- name: Recall |
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type: recall |
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value: 0.95 |
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- name: F1 |
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type: f1 |
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value: 0.9496487652420723 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# sentiment |
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This model is a fine-tuned version of [naufalihsan/indonesian-sbert-large](https://huggingface.co/naufalihsan/indonesian-sbert-large) on the indonlu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4450 |
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- Accuracy: 0.95 |
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- Precision: 0.9500 |
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- Recall: 0.95 |
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- F1: 0.9496 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 40 |
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- eval_batch_size: 40 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 275 | 0.2837 | 0.9405 | 0.9427 | 0.9405 | 0.9396 | |
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| 0.0501 | 2.0 | 550 | 0.1966 | 0.9460 | 0.9468 | 0.9460 | 0.9458 | |
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| 0.0501 | 3.0 | 825 | 0.2927 | 0.9437 | 0.9435 | 0.9437 | 0.9427 | |
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| 0.0369 | 4.0 | 1100 | 0.3666 | 0.9460 | 0.9459 | 0.9460 | 0.9456 | |
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| 0.0369 | 5.0 | 1375 | 0.3579 | 0.9468 | 0.9465 | 0.9468 | 0.9465 | |
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| 0.0098 | 6.0 | 1650 | 0.4497 | 0.9476 | 0.9479 | 0.9476 | 0.9471 | |
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| 0.0098 | 7.0 | 1925 | 0.4308 | 0.95 | 0.9501 | 0.95 | 0.9496 | |
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| 0.0012 | 8.0 | 2200 | 0.4402 | 0.95 | 0.9499 | 0.95 | 0.9496 | |
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| 0.0012 | 9.0 | 2475 | 0.4429 | 0.95 | 0.9500 | 0.95 | 0.9496 | |
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| 0.0007 | 10.0 | 2750 | 0.4450 | 0.95 | 0.9500 | 0.95 | 0.9496 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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